Biological variation in gene expression appears to be present even among carefully matched, genetically uniform individuals (Oleksiak et al. 2002); however, there is also a component of technical variation that can be attributed to the material handling and measurement processes. In order to characterize the biological component of variability, an experiment must also provide a means to assess technical variance components (Churchill 2002). This work will enhance interpretation of future gene expression studies by use of statistical models to explore: 1. Gene expression assays on replicated tumor samples with homogeneous populations of cells: granulosa cell tumors. The variability due to inherent biological sources will be estimated from this experimental data. 2. Gene expression assays on replicate samples of a tumor type with a heterogeneous population of neoplastic cells: mammary tumors from mice transgenic with the c-myc oncogene. Statistical methods will be developed to identify the gene expression attributable to specific cell types within a heterogeneous tumor. 3. A set of calibration experiments performed on multiple platforms (cDNA microarrays, long oligo arrays, Affymetrix GeneChips, and Massively Parallel Signature Sequencing) to assess and compare the components of variance contributed by tissue type, cDNA library production, and platform.